How can employers reduce AI workslop?
"Workslop" produced by artificial intelligence tools is disrupting trust among colleagues, according to a new report, which has underscored the need to address low-quality AI output before it brings lasting consequences at work.
A new report from Zety defined "workslop" as AI-generated work that might look polished at first, but lacks accuracy, substance, or proper review.
Its poll among 1,000 workers revealed that 55% of employees have received workslop from a manager or supervisor.
Workslop hits trust
Receiving workslop from colleagues can have a ripple effect on trust, particularly in colleagues and in AI, according to the report.
The majority of employees (74%) said receiving workslop lowered their trust in the sender's work quality.
Another 85% said receiving workslop from a manager would reduce their trust in leadership.
"When leaders rely on low-effort output, it subtly reshapes how authority is perceived," the report read.
"Employees begin to question not just the work itself, but the level of care behind it. Over time, that shift can make collaboration, alignment, and confidence in direction harder to sustain."
Employees' trust in AI tools is also hit hard by workslop, with 45% of employees saying low-quality AI output made them more cautious about the technology's role in the workplace.
Addressing AI workslop
The findings come in the wake of widespread AI use at work, even outpacing the training provided by employers.
Zety's report noted that only 31% of employees have received detailed training and ongoing support on AI tools.
Nearly half of employees (45%) said they only received limited training, while 24% said they did not receive training at all.
More than half of the respondents (51%) said better AI training would help reduce workslop.
Clearer quality standards (57%), new tools to detect errors (47%), as well as more review and editing time (44%) would address workslop from AI, according to the report.
More than a third of employees (39%) also said reducing AI workslop requires stronger accountability for mistakes.
"Addressing AI workslop calls for clearer norms around review, ownership, and quality," the report read.
"Teams that establish consistent standards are better positioned to maintain credibility as AI becomes more embedded in daily work. Strong oversight helps protect both performance and reputation."
